Dip Pen Nanolithography®: A “Desktop Nanofab™” Approach Using High‐Throughput Flexible Nanopatterning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The ability to perform controllable nanopatterning with a broad range of "inks" at ambient conditions is a key aspect of the dip pen nanolithography (DPN) technique. The traditional ink system to demonstrate DPN is n-alkanethiols on a gold substrate, but the DPN method has found numerous other applications since. This article is meant to outline recent advances in the DPN toolkit, both in terms of research and patterning technology, and to discuss applications of DPN as a viable nanofabrication method. We will summarize new DPN developments, and introduce our concept of the "Desktop Nanofab." In addition, we outline our efforts to commercialize DPN as a viable nanofabrication technique by demonstrating massively parallel nanopatterning with the 55,000 tip 2D nano PrintArray. This demonstrates our ability to overcome the serial nature of DPN patterning and enable high-throughput nanofabrication.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it